111     gradient_.resize(n, 1);  in ComputeStep()
174   gradient_.setZero();  in ComputeGradient()
175   jacobian->LeftMultiply(residuals, gradient_.data());  in ComputeGradient()
176   gradient_.array() /= diagonal_.array();  in ComputeGradient()
188       (gradient_.array() / diagonal_.array()).matrix();  in ComputeCauchyPoint()
190   alpha_ = gradient_.squaredNorm() / Jg.squaredNorm();  in ComputeCauchyPoint()
199   VectorRef dogleg_step(dogleg, gradient_.rows());  in ComputeTraditionalDoglegStep()
203   const double gradient_norm = gradient_.norm();  in ComputeTraditionalDoglegStep()
218     dogleg_step = -(radius_ / gradient_norm) * gradient_;  in ComputeTraditionalDoglegStep()
233   const double b_dot_a = -alpha_ * gradient_.dot(gauss_newton_step_);  in ComputeTraditionalDoglegStep()
248   dogleg_step = (-alpha_ * (1.0 - beta)) * gradient_  in ComputeTraditionalDoglegStep()
266   VectorRef dogleg_step(dogleg, gradient_.rows());  in ComputeSubspaceDoglegStep()
310     dogleg_step = -(radius_ / gradient_.norm()) * gradient_;  in ComputeSubspaceDoglegStep()
648   basis_vectors.col(0) = gradient_;  in ComputeSubspaceModel()
699   subspace_g_ = subspace_basis_.transpose() * gradient_;  in ComputeSubspaceModel()